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feat(paged): add cublas route trace patch
Add patch 0062 with default-off LLAMA_CUBLAS_ROUTE_TRACE instrumentation for generic cuBLAS MUL_MAT subroutes. Record Phase 36 DGX gates, serving trace results, and the next projection follow-up scope. Assisted-by: Codex:gpt-5
This commit is contained in:
Ettore Di Giacinto
@@ -87,7 +87,7 @@ orthogonal to the paged allocator.
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---
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## 3. Patch series (0001-0061)
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## 3. Patch series (0001-0062)
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Source-only patches, with intentional numbering gaps (e.g. 0005, 0027). The
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decode-serving graph-reuse levers are 0040-0041. "Bit-exact" = greedy md5 /
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@@ -219,6 +219,7 @@ These are the dominant decode levers on the Qwen3.6 hybrid models. All bit-exact
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| 0059 | **Gate MoE small-M MMQ tile policy** - adds default-off `LLAMA_MOE_SMALL_M_TILE=<n>` to cap only classified small-M MoE grouped-MMQ calls. This was used to A/B vLLM-like smaller M blocks without changing default inference. | yes (default-off, tile16, tile8, and post-serving gates green: MoE `8cb0ce23`, dense `5951a5b4`, `MUL_MAT_ID` `806/806`; Phase 33 rejected tile16 and tile8 as slower) |
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| 0060 | **Trace MoE MMID dispatch routes** - adds default-off `LLAMA_MOE_MMID_ROUTE_TRACE=<n>` around `MUL_MAT_ID` dispatch, classifying each call as `mmvq`, `mmvf`, grouped `mmq`, `mmf`, or host-sync `fallback`. This is evidence-only instrumentation to resolve whether serving hits the per-expert host-sync fallback. | yes (default-off, trace-enabled, and post-serving gates green: MoE `8cb0ce23`, dense `5951a5b4`, `MUL_MAT_ID` `806/806`; Phase 34 n128 trace found `mmq=2776`, `mmvq=1320`, `host_sync=0/4096`) |
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| 0061 | **Trace regular MUL_MAT dispatch routes** - adds default-off `LLAMA_MUL_MAT_ROUTE_TRACE=<n>` around regular `MUL_MAT`, classifying projection-heavy calls as `vec_f`, `mat_f`, `vec_q`, `mmq`, `batched_cublas`, `op_*`, `fp4_prefill`, or `fwht`. This is evidence-only instrumentation for the `bf16-proj` serving bucket. | yes (default-off, trace-enabled, and post-serving gates green: MoE `8cb0ce23`, dense `5951a5b4`, `MUL_MAT` `1146/1146`, `MUL_MAT_ID` `806/806`; Phase 35 n128 trace found BF16 routes `mat_f=2485`, `op_cublas=1330`) |
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| 0062 | **Trace cuBLAS subroutes** - adds default-off `LLAMA_CUBLAS_ROUTE_TRACE=<n>` around the generic cuBLAS `MUL_MAT` path, classifying calls as `nvfp4_bf16_tc`, `bf16_tc`, `f16_tc_32f`, `f16_tc_16f`, or `sgemm`. This is evidence-only instrumentation for the Phase 35 `op_cublas` bucket. | yes (default-off, trace-enabled, and post-serving gates green: MoE `8cb0ce23`, dense `5951a5b4`, `MUL_MAT` `1146/1146`, `MUL_MAT_ID` `806/806`; Phase 36 n128 trace found `bf16_tc=5681`, `sgemm=2511`) |
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> **Dropped: patch 0026 (hybrid per-head bf16 SSM state, `ssm_bf16_tau`).** Once
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> the decode fusions (0028 recurrent-state gather-fusion + 0029 block-table cache)
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@@ -2104,3 +2104,59 @@ Decision:
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- Next projection work should either add a cuBLAS/MMF subroute trace or test a
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bounded BF16 route policy for the `op_cublas` shapes. Do not chase batched
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cuBLAS for this measured serving slice.
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## Phase 36 cuBLAS Subroute Trace
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Phase 36 added patch `0062`, a default-off `LLAMA_CUBLAS_ROUTE_TRACE=<n>`
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diagnostic around the generic cuBLAS `MUL_MAT` path. It does not alter branch
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behavior; it classifies existing calls as `nvfp4_bf16_tc`, `bf16_tc`,
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`f16_tc_32f`, `f16_tc_16f`, or `sgemm`.
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Artifact:
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- `/home/mudler/bench/phase36_cublas_route_trace/20260701_081228`
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Run:
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- Fork commit: `/home/mudler/_git/llama.cpp` `38c4ef2e4`
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- DGX mirror commit: `dgx:~/llama-phase6-source` `e0224393a`
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- Env: `LLAMA_KV_PAGED=1 LLAMA_MOE_FORCE_GRAPHS=1 LLAMA_CUBLAS_ROUTE_TRACE=8192`
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- Workload: staggered n128 `llama-server` diagnostic trace
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Route summary:
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| route | count |
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|-------|------:|
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| `bf16_tc` | 5681 |
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| `sgemm` | 2511 |
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Top shapes:
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| route | shape | count |
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|-------|-------|------:|
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| `bf16_tc` | `type=30 row_diff=32 src1_ncols=510 ne00=2048 ne10=2048` | 360 |
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| `bf16_tc` | `type=30 row_diff=8192 src1_ncols=510 ne00=2048 ne10=2048` | 240 |
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| `bf16_tc` | `type=30 row_diff=2048 src1_ncols=510 ne00=4096 ne10=4096` | 240 |
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| `sgemm` | `type=0 row_diff=256 src1_ncols=510 ne00=2048 ne10=2048` | 240 |
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| `sgemm` | `type=0 row_diff=1 src1_ncols=510 ne00=2048 ne10=2048` | 240 |
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Gates:
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| check | status | actual |
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|-------|--------|--------|
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| default-off MoE md5 | ok | `8cb0ce23777bf55f92f63d0292c756b0` |
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| default-off dense md5 | ok | `5951a5b4d624ce891e22ab5fca9bc439` |
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| trace-enabled MoE md5 | ok | `8cb0ce23777bf55f92f63d0292c756b0` |
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| trace-enabled dense md5 | ok | `5951a5b4d624ce891e22ab5fca9bc439` |
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| post-serving MoE md5 | ok | `8cb0ce23777bf55f92f63d0292c756b0` |
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| post-serving dense md5 | ok | `5951a5b4d624ce891e22ab5fca9bc439` |
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| `MUL_MAT` | ok | `1146/1146` default, trace, post-serving |
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| `MUL_MAT_ID` | ok | `806/806` default, trace, post-serving |
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Decision:
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- Phase 35's generic `op_cublas` bucket is BF16 tensor-core plus F32 SGEMM in
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this serving slice. It is not NVFP4 cuBLAS and not batched cuBLAS.
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- The next projection phase should identify whether the `type=0` SGEMM shapes
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are expected glue tensors or a missed BF16 route. Do not change routing until
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a separately gated policy proves md5/op safety.
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@@ -466,6 +466,18 @@ MoE `8cb0ce23777bf55f92f63d0292c756b0`, dense
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was split `mat_f=2485`, `op_cublas=1330`. Next projection work should target
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BF16 `mat_f`/`op_cublas` subroute evidence or route policy, not batched cuBLAS.
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Phase 36 added patch `0062`, default-off `LLAMA_CUBLAS_ROUTE_TRACE=<n>`, to
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classify the generic cuBLAS `MUL_MAT` subroute without changing branch behavior.
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Artifact: `/home/mudler/bench/phase36_cublas_route_trace/20260701_081228`.
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Fork commit: `38c4ef2e4 feat(cuda): trace cublas routes`; DGX mirror commit:
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`e0224393a`. Default-off, trace-enabled, and post-serving gates stayed green:
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MoE `8cb0ce23777bf55f92f63d0292c756b0`, dense
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`5951a5b4d624ce891e22ab5fca9bc439`, `MUL_MAT` `1146/1146`, `MUL_MAT_ID`
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`806/806`. Live n128 serving with trace cap 8192 found `bf16_tc=5681` and
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`sgemm=2511`. The next projection phase should explain whether the F32 SGEMM
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shapes are expected glue tensors or a missed BF16 route; do not chase NVFP4
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cuBLAS or batched cuBLAS for this measured bucket.
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---
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## 5. METHODOLOGY LESSONS (so you do not repeat the mistakes)
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@@ -515,15 +527,15 @@ Only pursue if (a)+(b) are not options and someone explicitly wants the residual
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## 7. KEY FILE / ARTIFACT INDEX
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### Fork (canonical source of truth)
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- Local canonical fork: `/home/mudler/_git/llama.cpp`, branch **`localai-paged`**, HEAD `486c28c63d5297afd06e5a2bdbd4fb89cad749cd` ("trace mul mat routes", patch `0061`).
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- DGX current clean mirror/build tree: `dgx:~/llama-phase6-source`, HEAD `18f7ad005` with the Phase 35 regular MUL_MAT route-trace patch applied and committed; Phase 20/26/27 artifacts still record their historical source hashes.
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- Local canonical fork: `/home/mudler/_git/llama.cpp`, branch **`localai-paged`**, HEAD `38c4ef2e4` ("trace cublas routes", patch `0062`).
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- DGX current clean mirror/build tree: `dgx:~/llama-phase6-source`, HEAD `e0224393a` with the Phase 36 cuBLAS route-trace patch applied and committed; Phase 20/26/27 artifacts still record their historical source hashes.
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- Historical DGX dev tree: `dgx:~/llama-paged-dev`, branch **`paged`**, HEAD `a7d439e8ce6990eb09721223c975da4e49d8d136` ("GDN CONFIG C (M8) - bf16 Kc/Qc"). It is an old experimental tree and must not be treated as canonical.
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### LocalAI worktree
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- Path: `/home/mudler/_git/LocalAI/.claude/worktrees/feat+paged-attention`, branch `worktree-feat+paged-attention` (currently 246 ahead, 31 behind `origin/master`; recompute before reporting).
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- Backend dir: `backend/cpp/llama-cpp-localai-paged/` (`Makefile` thin wrapper, `package.sh`, `run.sh`, `README.md` ~44 KB canonical, `docs/`, `patches/paged/`).
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- `docs/`: `VLLM_PARITY_FINAL.md` (authoritative record), `VLLM_PARITY_LEVER_MAP.md` (working brainstorm, profile-validated section), `DECODE_SERVING_SCOPE.md`, `PREFILL_GEMM_SCOPE.md`, `PREFILL_GEMM_RESULTS.md`, `TENSORCORE_GDN_SCOPE.md`, `TENSORCORE_GDN_BUILD_PLAN.md`, `ACCELERATOR_PORTING_SCOPE.md`, `UPSTREAM_LAYER2_SCOPE.md`, `LOCALAI_LLAMACPP_BACKEND_PLAN.md`, `PAGED_BITEXACT_NOTE.md`, `PATCH_MAINTENANCE.md`, `final_benchmark.csv`, `paged-burst-bench.cpp`, `paged-reclaim-unit.cpp`, 3 PNGs, and this `PARITY_HANDOFF.md`.
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- `patches/paged/`: **52** `.patch` files spanning 0001-0061 with intentional gaps (missing 0005, 0026 [dropped ssm_bf16_tau], 0027, 0032, 0036-0039, 0045). Core paged-KV 0001-0012; decode-first scheduler 0013/0016; serving graph reuse 0040/0041; prefill fusions 0042/0044; SSM/GDN decode 0018-0022/0028; MoE NVFP4 quant 0023/0025/0043; FP4-MMA/Marlin scaffolds 0033/0034/0035 (default-off); GDN tensor-core prefill 0031 -> 0046 (geometry gate) -> 0047 (f32-only M5, default-on under paged KV); W4A16 packed metadata/shape/padding is 0048-0050; MoE safety tests are 0051-0053; MTP backend-sampling safety is 0054; speculative shape trace is 0055; MoE MMQ selector/launch/candidate/tile-policy/route instrumentation is 0056-0060; regular MUL_MAT route instrumentation is 0061.
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- `patches/paged/`: **53** `.patch` files spanning 0001-0062 with intentional gaps (missing 0005, 0026 [dropped ssm_bf16_tau], 0027, 0032, 0036-0039, 0045). Core paged-KV 0001-0012; decode-first scheduler 0013/0016; serving graph reuse 0040/0041; prefill fusions 0042/0044; SSM/GDN decode 0018-0022/0028; MoE NVFP4 quant 0023/0025/0043; FP4-MMA/Marlin scaffolds 0033/0034/0035 (default-off); GDN tensor-core prefill 0031 -> 0046 (geometry gate) -> 0047 (f32-only M5, default-on under paged KV); W4A16 packed metadata/shape/padding is 0048-0050; MoE safety tests are 0051-0053; MTP backend-sampling safety is 0054; speculative shape trace is 0055; MoE MMQ selector/launch/candidate/tile-policy/route instrumentation is 0056-0060; regular MUL_MAT route instrumentation is 0061; cuBLAS route instrumentation is 0062.
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### Bench artifacts (DGX)
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- `~/bench/COMBINED_DEFINITIVE.txt` (+ `.log`, `.done`, `combined_definitive.sh`, `combined_definitive.out`) - historical same-session both-engine run.
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@@ -541,6 +553,7 @@ Only pursue if (a)+(b) are not options and someone explicitly wants the residual
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- `~/bench/phase33_small_m_tile_policy/20260701_071136` - default-off MoE MMQ small-M tile policy patch `0059`; tile16/tile8 md5/op safe but both slower in n128 serving.
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- `~/bench/phase34_mmid_route_trace/20260701_072737` - default-off MoE MMID route trace patch `0060`; default/trace/post-serving md5 gates green; n128 route trace found `mmq=2776`, `mmvq=1320`, `host_sync=0/4096`.
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- `~/bench/phase35_mul_mat_route_trace/20260701_074359` - default-off regular MUL_MAT route trace patch `0061`; default/trace/post-serving md5 gates green; n128 route trace found BF16 `mat_f=2485`, `op_cublas=1330`.
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- `~/bench/phase36_cublas_route_trace/20260701_081228` - default-off cuBLAS subroute trace patch `0062`; default/trace/post-serving md5 and op gates green; n128 route trace found `bf16_tc=5681`, `sgemm=2511`.
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- Per-engine logs `~/bench/COMBINED_{paged,vllm}_{MOE,DENSE}_server.log`; `~/bench/BENCHMARK_PROGRESS.md`.
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- Graph-node-traced high-N profiles: `~/highN_prof2/*.nsys-rep` (paged npl=256), `~/highN_vllm/*.nsys-rep` (vLLM), 2026-06-30.
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- A/B dirs: `~/bench/marlin_gate/`, `~/bench/gdn_p1_ab/`.
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@@ -553,8 +566,8 @@ Only pursue if (a)+(b) are not options and someone explicitly wants the residual
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### Discrepancies to flag / resolve (carried verbatim from the gather, including UNVERIFIED labels)
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1. **Pin prose reconciled in this worktree.** Makefile line 52 `LLAMA_VERSION?=0ed235ea2c17a19fc8238668653946721ed136fd` is authoritative and matches the local fork merge-base. Hard rule: the paged pin must equal the stock `llama-cpp` pin (shared `grpc-server.cpp`); a bump to `c299a92c` once broke the grpc-server link despite being bit-exact and was reverted. Trust the Makefile when building.
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2. **Current fork/mirror are clean and verified.** Local fork HEAD is `486c28c63`, DGX clean mirror HEAD is `18f7ad005`, and Phase 35 should be treated as the current patch-series tip. The old `llama-paged-dev` tree is historical only.
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3. **Worktree patch series is tracked through 0061.** The only expected unrelated untracked path in this worktree is `.claude/`.
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2. **Current fork/mirror are clean and verified.** Local fork HEAD is `38c4ef2e4`, DGX clean mirror HEAD is `e0224393a`, and Phase 36 should be treated as the current patch-series tip. The old `llama-paged-dev` tree is historical only.
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3. **Worktree patch series is tracked through 0062.** The only expected unrelated untracked path in this worktree is `.claude/`.
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4. **`sm_121a` is not in the worktree build files** - it lives only in the DGX experimental build scripts (`gdn_cc.sh`, `gdn_bv_build.sh`, `paged-build.sh`); mainline uses arch `121`. **UNVERIFIED** whether the shipped CI Dockerfile build path injects `121a` for the FP4-MMA kernels (`Dockerfile.llama-cpp-localai-paged` does not hardcode a CUDA arch).
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5. **The `0921716...` paged-MoE md5 open item.** `COMBINED_DEFINITIVE.txt` records `PAGED_GATE_MD5=0921716cd0582b5d15af8c362b811d00` for MoE, but a full doc/patch/`git log -S` grep of the worktree found **no** occurrence of `0921716...` in any committed source; the committed canonical paged-MoE gate is `8cb0ce23`. Treat this as **unreconciled**: the documented, KL-validated paged-MoE gate remains `8cb0ce23`, and any paged-MoE divergence (including `0921716`) must be KL-validated against the f16 reference before being accepted as benign, never on assertion alone. The `0921716` value is **UNVERIFIED** as a sanctioned gate; do not adopt it as canonical without re-running the KL gate. The **dense** run is symmetric: `COMBINED_DEFINITIVE.txt` records `PAGED_GATE_MD5=ecfe924dee6c5622c149f419ff2a6481` for dense, which likewise differs from the canonical dense gate `5951a5b4`. Both CDEF `PAGED_GATE_MD5` values come from the `combined_definitive.sh` harness's own gate command, NOT the canonical bit-exact gate command in section 3.3, which is why they diverge from the committed `8cb0ce23` / `5951a5b4`; neither is a sanctioned gate and both must be KL-validated before being treated as benign.
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@@ -57,18 +57,18 @@ everywhere without ever touching the stock `llama-cpp` source tree.
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## Latest mirror check
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Phase 35 re-verified the mirror invariant after adding patch `0061`:
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Phase 36 re-verified the mirror invariant after adding patch `0062`:
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```text
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base=0ed235ea2c17a19fc8238668653946721ed136fd
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applied_tree=305ebb96801822f2132ed9e9c868308b0759c7b9
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fork_tree=305ebb96801822f2132ed9e9c868308b0759c7b9
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applied_tree=208189d119efe27477f1900cc6f7428bd1720449
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fork_tree=208189d119efe27477f1900cc6f7428bd1720449
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```
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The check used a fresh worktree at `LLAMA_VERSION`, applied every
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`patches/paged/0*.patch` with strict `git apply`, staged the result, and compared
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`git write-tree` to canonical fork branch `localai-paged` at
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`486c28c63 feat(cuda): trace mul mat routes`.
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`38c4ef2e4 feat(cuda): trace cublas routes`.
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## Status
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@@ -931,6 +931,30 @@ in a future serving configuration, first isolate `mtp_eh_proj` / shared-head
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projection with `llama-debug --tensor-filter 'mtp_|h_nextn|nextn|ffn_|attn_'`
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before optimizing ordinary decoder projections.
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### Phase 36 cuBLAS subroute trace
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Phase 36 added patch `0062`, default-off `LLAMA_CUBLAS_ROUTE_TRACE=<n>`, to
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classify the generic cuBLAS `MUL_MAT` subroute without changing branch behavior.
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Artifact: `/home/mudler/bench/phase36_cublas_route_trace/20260701_081228`.
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Default-off, trace-enabled, and post-serving gates were all bit-exact: MoE
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`8cb0ce23777bf55f92f63d0292c756b0`, dense
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`5951a5b4d624ce891e22ab5fca9bc439`, `MUL_MAT` `1146/1146`, and `MUL_MAT_ID`
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`806/806`.
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Live n128 serving with `LLAMA_CUBLAS_ROUTE_TRACE=8192` produced:
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| cuBLAS route | count |
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|--------------|------:|
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| `bf16_tc` | 5681 |
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| `sgemm` | 2511 |
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Top SGEMM shapes were `type=0 row_diff=256/1 src1_ncols=510 ne00=2048
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ne10=2048`. Lever implication: the measured `op_cublas` bucket is BF16
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tensor-core plus F32 SGEMM, not NVFP4 cuBLAS and not batched cuBLAS. The next
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projection phase should explain whether the F32 SGEMM shapes are expected glue
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tensors or a missed BF16 route, with md5/op gates before any route policy A/B.
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Relevant files (all absolute): `/home/mudler/_git/LocalAI/.claude/worktrees/feat+paged-attention/backend/cpp/llama-cpp-localai-paged/docs/{DECODE_SERVING_SCOPE.md,PREFILL_GEMM_SCOPE.md,PREFILL_GEMM_RESULTS.md,TENSORCORE_GDN_SCOPE.md,final_benchmark.csv}`, `.../README.md`, `.../patches/paged/0034-feat-paged-native-NVFP4-W4A4-FP4-MMA-large-M-prefill.patch` (P1/P2), `.../patches/paged/0042-feat-paged-fused-residual-add-RMS-norm-weight-multip.patch` (P7), `.../patches/paged/0031` (P4), `0025` (D1), `0018/0022` (D4/D5), `0009/0010` (D3/D6/D7); graph source `/home/mudler/_git/LocalAI/backend/cpp/llama-cpp-paged-dev/src/{models/qwen35moe.cpp,models/delta-net-base.cpp,llama-graph.cpp}`.
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### Phase 10 GDN C32 slab update
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@@ -0,0 +1,332 @@
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From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
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From: Ettore Di Giacinto <mudler@localai.io>
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Date: Wed, 1 Jul 2026 06:20:31 +0000
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Subject: [PATCH] feat(cuda): trace cublas routes
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Add a default-off LLAMA_CUBLAS_ROUTE_TRACE diagnostic around the generic cuBLAS MUL_MAT path.
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The trace classifies NVFP4/BF16/FP16/SGEMM subroutes without changing branch behavior, and extends the route helper test coverage.
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Assisted-by: Codex:gpt-5
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---
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ggml/src/ggml-cuda/ggml-cuda.cu | 53 +++++++++++--
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ggml/src/ggml-cuda/mmq-shape-trace.h | 108 +++++++++++++++++++++++++++
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tests/test-cuda-mmq-shape-trace.cpp | 62 +++++++++++++++
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3 files changed, 216 insertions(+), 7 deletions(-)
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diff --git a/ggml/src/ggml-cuda/ggml-cuda.cu b/ggml/src/ggml-cuda/ggml-cuda.cu
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index cd34aff13..eff197818 100644
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--- a/ggml/src/ggml-cuda/ggml-cuda.cu
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+++ b/ggml/src/ggml-cuda/ggml-cuda.cu
|
||||
@@ -1627,6 +1627,32 @@ static const cublas_force_compute_type & ggml_cuda_cublas_get_force_compute_type
|
||||
return compute_type;
|
||||
}
|
||||
|
||||
+static inline int ggml_cuda_cublas_route_trace_limit() {
|
||||
+ static const int value = []() {
|
||||
+ const char * s = getenv("LLAMA_CUBLAS_ROUTE_TRACE");
|
||||
+ return s ? atoi(s) : 0;
|
||||
+ }();
|
||||
+
|
||||
+ return value;
|
||||
+}
|
||||
+
|
||||
+static inline void ggml_cuda_cublas_route_trace(const ggml_cuda_cublas_route_shape & shape) {
|
||||
+ const int trace_limit = ggml_cuda_cublas_route_trace_limit();
|
||||
+ if (trace_limit <= 0) {
|
||||
+ return;
|
||||
+ }
|
||||
+
|
||||
+ static std::atomic<int> trace_count{0};
|
||||
+ const int trace_idx = trace_count.fetch_add(1, std::memory_order_relaxed);
|
||||
+ if (trace_idx >= trace_limit) {
|
||||
+ return;
|
||||
+ }
|
||||
+
|
||||
+ char buf[320];
|
||||
+ ggml_cuda_cublas_route_shape_format(buf, sizeof(buf), shape);
|
||||
+ fprintf(stderr, "[LLAMA_CUBLAS_ROUTE] %s\n", buf);
|
||||
+}
|
||||
+
|
||||
static void ggml_cuda_op_mul_mat_cublas(
|
||||
ggml_backend_cuda_context & ctx,
|
||||
const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, const char * src0_dd_i, const float * src1_ddf_i,
|
||||
@@ -1662,7 +1688,22 @@ static void ggml_cuda_op_mul_mat_cublas(
|
||||
row_diff == src0->ne[1] &&
|
||||
dst->op_params[0] == GGML_PREC_DEFAULT;
|
||||
|
||||
- if (supports_bf16 && src0->type == GGML_TYPE_NVFP4 && ggml_is_contiguous(src0) && row_diff == src0->ne[1]) {
|
||||
+ const bool src0_contig = ggml_is_contiguous(src0);
|
||||
+ const bool full_rows = row_diff == src0->ne[1];
|
||||
+ const bool fast_fp16 = fast_fp16_hardware_available(cc);
|
||||
+ bool force_fp32 = false;
|
||||
+ bool force_fp16 = false;
|
||||
+ if (fast_fp16 && use_fp16) {
|
||||
+ const auto & force_compute_type = ggml_cuda_cublas_get_force_compute_type();
|
||||
+ force_fp32 = force_compute_type.fp32;
|
||||
+ force_fp16 = force_compute_type.fp16;
|
||||
+ }
|
||||
+ ggml_cuda_cublas_route_trace(ggml_cuda_cublas_route_shape_make(
|
||||
+ src0->type, src1->type, row_diff, src1_ncols, ne00, ne10, ldc,
|
||||
+ supports_bf16, use_fp16, fast_fp16, force_fp32, force_fp16, src0_contig, full_rows,
|
||||
+ GGML_CUDA_CC_IS_CDNA(cc), GGML_CUDA_CC_IS_RDNA4(cc), cc == GGML_CUDA_CC_VOLTA));
|
||||
+
|
||||
+ if (supports_bf16 && src0->type == GGML_TYPE_NVFP4 && src0_contig && full_rows) {
|
||||
// Paged prefill lever (patch 0033): NVFP4 only reaches cuBLAS when
|
||||
// ggml_cuda_should_use_mmq() returned false (large-M dense prefill).
|
||||
// Dequant the FP4 weights to a TRANSIENT bf16 pool buffer and run a
|
||||
@@ -1702,7 +1743,7 @@ static void ggml_cuda_op_mul_mat_cublas(
|
||||
|
||||
const to_fp32_cuda_t to_fp32_cuda = ggml_get_to_fp32_cuda(GGML_TYPE_BF16);
|
||||
to_fp32_cuda(dst_bf16.get(), dst_dd_i, row_diff*src1_ncols, stream);
|
||||
- } else if (supports_bf16 && src0->type == GGML_TYPE_BF16 && ggml_is_contiguous(src0) && row_diff == src0->ne[1]) {
|
||||
+ } else if (supports_bf16 && src0->type == GGML_TYPE_BF16 && src0_contig && full_rows) {
|
||||
ggml_cuda_pool_alloc<nv_bfloat16> src1_as_bf16(ctx.pool(id));
|
||||
if (src1->type != GGML_TYPE_BF16) {
|
||||
const to_bf16_cuda_t to_bf16_cuda = ggml_get_to_bf16_cuda(src1->type);
|
||||
@@ -1730,7 +1771,7 @@ static void ggml_cuda_op_mul_mat_cublas(
|
||||
|
||||
const to_fp32_cuda_t to_fp32_cuda = ggml_get_to_fp32_cuda(GGML_TYPE_BF16);
|
||||
to_fp32_cuda(dst_bf16.get(), dst_dd_i, row_diff*src1_ncols, stream);
|
||||
- } else if (fast_fp16_hardware_available(cc) && use_fp16) {
|
||||
+ } else if (fast_fp16 && use_fp16) {
|
||||
// convert src0 and src1 to fp16, multiply as fp16, convert dst to fp32
|
||||
ggml_cuda_pool_alloc<half> src0_as_f16(ctx.pool(id));
|
||||
if (src0->type != GGML_TYPE_F16) {
|
||||
@@ -1754,12 +1795,10 @@ static void ggml_cuda_op_mul_mat_cublas(
|
||||
|
||||
CUBLAS_CHECK(cublasSetStream(ctx.cublas_handle(id), stream));
|
||||
|
||||
- const auto & force_compute_type = ggml_cuda_cublas_get_force_compute_type();
|
||||
-
|
||||
- if (!force_compute_type.fp16 && (GGML_CUDA_CC_IS_CDNA(cc)
|
||||
+ if (!force_fp16 && (GGML_CUDA_CC_IS_CDNA(cc)
|
||||
|| GGML_CUDA_CC_IS_RDNA4(cc)
|
||||
|| cc == GGML_CUDA_CC_VOLTA
|
||||
- || force_compute_type.fp32))
|
||||
+ || force_fp32))
|
||||
{
|
||||
const float alpha = 1.0f;
|
||||
const float beta = 0.0f;
|
||||
diff --git a/ggml/src/ggml-cuda/mmq-shape-trace.h b/ggml/src/ggml-cuda/mmq-shape-trace.h
|
||||
index 8ac373fd9..f5b4ecf2c 100644
|
||||
--- a/ggml/src/ggml-cuda/mmq-shape-trace.h
|
||||
+++ b/ggml/src/ggml-cuda/mmq-shape-trace.h
|
||||
@@ -85,6 +85,14 @@ enum ggml_cuda_mul_mat_route {
|
||||
GGML_CUDA_MUL_MAT_ROUTE_OP_CUBLAS,
|
||||
};
|
||||
|
||||
+enum ggml_cuda_cublas_route {
|
||||
+ GGML_CUDA_CUBLAS_ROUTE_NVFP4_BF16_TC,
|
||||
+ GGML_CUDA_CUBLAS_ROUTE_BF16_TC,
|
||||
+ GGML_CUDA_CUBLAS_ROUTE_F16_TC_32F,
|
||||
+ GGML_CUDA_CUBLAS_ROUTE_F16_TC_16F,
|
||||
+ GGML_CUDA_CUBLAS_ROUTE_SGEMM,
|
||||
+};
|
||||
+
|
||||
struct ggml_cuda_mul_mat_route_shape {
|
||||
ggml_cuda_mul_mat_route route;
|
||||
int type;
|
||||
@@ -102,6 +110,27 @@ struct ggml_cuda_mul_mat_route_shape {
|
||||
bool use_fwht;
|
||||
};
|
||||
|
||||
+struct ggml_cuda_cublas_route_shape {
|
||||
+ ggml_cuda_cublas_route route;
|
||||
+ int type;
|
||||
+ int src1_type;
|
||||
+ int64_t row_diff;
|
||||
+ int64_t src1_ncols;
|
||||
+ int64_t ne00;
|
||||
+ int64_t ne10;
|
||||
+ int64_t ldc;
|
||||
+ bool supports_bf16;
|
||||
+ bool use_fp16;
|
||||
+ bool fast_fp16;
|
||||
+ bool force_fp32;
|
||||
+ bool force_fp16;
|
||||
+ bool src0_contig;
|
||||
+ bool full_rows;
|
||||
+ bool is_cdna;
|
||||
+ bool is_rdna4;
|
||||
+ bool is_volta;
|
||||
+};
|
||||
+
|
||||
static inline const char * ggml_cuda_mmid_route_name(const ggml_cuda_mmid_route route) {
|
||||
switch (route) {
|
||||
case GGML_CUDA_MMID_ROUTE_MMVQ: return "mmvq";
|
||||
@@ -132,6 +161,18 @@ static inline const char * ggml_cuda_mul_mat_route_name(const ggml_cuda_mul_mat_
|
||||
return "unknown";
|
||||
}
|
||||
|
||||
+static inline const char * ggml_cuda_cublas_route_name(const ggml_cuda_cublas_route route) {
|
||||
+ switch (route) {
|
||||
+ case GGML_CUDA_CUBLAS_ROUTE_NVFP4_BF16_TC: return "nvfp4_bf16_tc";
|
||||
+ case GGML_CUDA_CUBLAS_ROUTE_BF16_TC: return "bf16_tc";
|
||||
+ case GGML_CUDA_CUBLAS_ROUTE_F16_TC_32F: return "f16_tc_32f";
|
||||
+ case GGML_CUDA_CUBLAS_ROUTE_F16_TC_16F: return "f16_tc_16f";
|
||||
+ case GGML_CUDA_CUBLAS_ROUTE_SGEMM: return "sgemm";
|
||||
+ }
|
||||
+
|
||||
+ return "unknown";
|
||||
+}
|
||||
+
|
||||
static inline ggml_cuda_mmq_shape ggml_cuda_mmq_shape_make(
|
||||
const int type, const bool is_moe, const int64_t ncols_dst, const int64_t nchannels_x,
|
||||
const int64_t ncols_max, const int mmq_x_max, const int mmq_x_lim, const int mmq_x_best,
|
||||
@@ -205,6 +246,47 @@ static inline ggml_cuda_mul_mat_route_shape ggml_cuda_mul_mat_route_shape_make(
|
||||
};
|
||||
}
|
||||
|
||||
+static inline ggml_cuda_cublas_route_shape ggml_cuda_cublas_route_shape_make(
|
||||
+ const int type, const int src1_type, const int64_t row_diff, const int64_t src1_ncols,
|
||||
+ const int64_t ne00, const int64_t ne10, const int64_t ldc, const bool supports_bf16,
|
||||
+ const bool use_fp16, const bool fast_fp16, const bool force_fp32, const bool force_fp16,
|
||||
+ const bool src0_contig, const bool full_rows, const bool is_cdna, const bool is_rdna4,
|
||||
+ const bool is_volta) {
|
||||
+ ggml_cuda_cublas_route route = GGML_CUDA_CUBLAS_ROUTE_SGEMM;
|
||||
+ if (supports_bf16 && type == 40 && src0_contig && full_rows) {
|
||||
+ route = GGML_CUDA_CUBLAS_ROUTE_NVFP4_BF16_TC;
|
||||
+ } else if (supports_bf16 && type == 30 && src0_contig && full_rows) {
|
||||
+ route = GGML_CUDA_CUBLAS_ROUTE_BF16_TC;
|
||||
+ } else if (fast_fp16 && use_fp16) {
|
||||
+ if (!force_fp16 && (is_cdna || is_rdna4 || is_volta || force_fp32)) {
|
||||
+ route = GGML_CUDA_CUBLAS_ROUTE_F16_TC_32F;
|
||||
+ } else {
|
||||
+ route = GGML_CUDA_CUBLAS_ROUTE_F16_TC_16F;
|
||||
+ }
|
||||
+ }
|
||||
+
|
||||
+ return {
|
||||
+ route,
|
||||
+ type,
|
||||
+ src1_type,
|
||||
+ row_diff,
|
||||
+ src1_ncols,
|
||||
+ ne00,
|
||||
+ ne10,
|
||||
+ ldc,
|
||||
+ supports_bf16,
|
||||
+ use_fp16,
|
||||
+ fast_fp16,
|
||||
+ force_fp32,
|
||||
+ force_fp16,
|
||||
+ src0_contig,
|
||||
+ full_rows,
|
||||
+ is_cdna,
|
||||
+ is_rdna4,
|
||||
+ is_volta,
|
||||
+ };
|
||||
+}
|
||||
+
|
||||
static inline ggml_cuda_mmid_route_shape ggml_cuda_mmid_route_shape_make(
|
||||
const int type, const int64_t ne2, const int64_t ne12, const int64_t n_experts,
|
||||
const int mmvq_max, const bool use_mmq, const bool use_mmf, const bool is_amd,
|
||||
@@ -377,6 +459,32 @@ static inline int ggml_cuda_mul_mat_route_shape_format(
|
||||
shape.use_fwht ? 1 : 0);
|
||||
}
|
||||
|
||||
+static inline int ggml_cuda_cublas_route_shape_format(
|
||||
+ char * buf, const size_t size, const ggml_cuda_cublas_route_shape & shape) {
|
||||
+ return std::snprintf(buf, size,
|
||||
+ "route=%s type=%d src1_type=%d row_diff=%lld src1_ncols=%lld ne00=%lld ne10=%lld ldc=%lld "
|
||||
+ "supports_bf16=%d use_fp16=%d fast_fp16=%d force_fp32=%d force_fp16=%d "
|
||||
+ "src0_contig=%d full_rows=%d is_cdna=%d is_rdna4=%d is_volta=%d",
|
||||
+ ggml_cuda_cublas_route_name(shape.route),
|
||||
+ shape.type,
|
||||
+ shape.src1_type,
|
||||
+ (long long) shape.row_diff,
|
||||
+ (long long) shape.src1_ncols,
|
||||
+ (long long) shape.ne00,
|
||||
+ (long long) shape.ne10,
|
||||
+ (long long) shape.ldc,
|
||||
+ shape.supports_bf16 ? 1 : 0,
|
||||
+ shape.use_fp16 ? 1 : 0,
|
||||
+ shape.fast_fp16 ? 1 : 0,
|
||||
+ shape.force_fp32 ? 1 : 0,
|
||||
+ shape.force_fp16 ? 1 : 0,
|
||||
+ shape.src0_contig ? 1 : 0,
|
||||
+ shape.full_rows ? 1 : 0,
|
||||
+ shape.is_cdna ? 1 : 0,
|
||||
+ shape.is_rdna4 ? 1 : 0,
|
||||
+ shape.is_volta ? 1 : 0);
|
||||
+}
|
||||
+
|
||||
static inline int ggml_cuda_mmq_small_m_shape_format(
|
||||
char * buf, const size_t size, const ggml_cuda_mmq_small_m_shape & shape) {
|
||||
return std::snprintf(buf, size,
|
||||
diff --git a/tests/test-cuda-mmq-shape-trace.cpp b/tests/test-cuda-mmq-shape-trace.cpp
|
||||
index 2bd41d1d8..1443749c3 100644
|
||||
--- a/tests/test-cuda-mmq-shape-trace.cpp
|
||||
+++ b/tests/test-cuda-mmq-shape-trace.cpp
|
||||
@@ -285,5 +285,67 @@ int main() {
|
||||
require(std::strstr(buf, "use_batched_cublas=0") != nullptr,
|
||||
"regular MUL_MAT trace includes batched cuBLAS predicate");
|
||||
|
||||
+ const ggml_cuda_cublas_route_shape bf16_tc = ggml_cuda_cublas_route_shape_make(
|
||||
+ /* type */ 30,
|
||||
+ /* src1_type */ 0,
|
||||
+ /* row_diff */ 18,
|
||||
+ /* src1_ncols */ 18,
|
||||
+ /* ne00 */ 1024,
|
||||
+ /* ne10 */ 1024,
|
||||
+ /* ldc */ 18,
|
||||
+ /* supports_bf16 */ true,
|
||||
+ /* use_fp16 */ false,
|
||||
+ /* fast_fp16 */ true,
|
||||
+ /* force_fp32 */ false,
|
||||
+ /* force_fp16 */ false,
|
||||
+ /* src0_contig */ true,
|
||||
+ /* full_rows */ true,
|
||||
+ /* is_cdna */ false,
|
||||
+ /* is_rdna4 */ false,
|
||||
+ /* is_volta */ false);
|
||||
+
|
||||
+ require(bf16_tc.route == GGML_CUDA_CUBLAS_ROUTE_BF16_TC,
|
||||
+ "cuBLAS records native BF16 tensor-core route");
|
||||
+
|
||||
+ const ggml_cuda_cublas_route_shape nvfp4_bf16_tc = ggml_cuda_cublas_route_shape_make(
|
||||
+ /* type */ 40, 0, 128, 128, 1024, 1024, 128, true, false, true, false, false, true, true,
|
||||
+ false, false, false);
|
||||
+
|
||||
+ require(nvfp4_bf16_tc.route == GGML_CUDA_CUBLAS_ROUTE_NVFP4_BF16_TC,
|
||||
+ "cuBLAS records NVFP4 dequant-to-BF16 tensor-core route");
|
||||
+
|
||||
+ const ggml_cuda_cublas_route_shape f16_tc_16f = ggml_cuda_cublas_route_shape_make(
|
||||
+ /* type */ 1, 0, 64, 64, 1024, 1024, 64, false, true, true, false, false, true, true,
|
||||
+ false, false, false);
|
||||
+
|
||||
+ require(f16_tc_16f.route == GGML_CUDA_CUBLAS_ROUTE_F16_TC_16F,
|
||||
+ "cuBLAS records default FP16 tensor-core 16F compute route");
|
||||
+
|
||||
+ const ggml_cuda_cublas_route_shape f16_tc_32f = ggml_cuda_cublas_route_shape_make(
|
||||
+ /* type */ 1, 0, 64, 64, 1024, 1024, 64, false, true, true, true, false, true, true,
|
||||
+ false, false, false);
|
||||
+
|
||||
+ require(f16_tc_32f.route == GGML_CUDA_CUBLAS_ROUTE_F16_TC_32F,
|
||||
+ "cuBLAS records forced FP16 tensor-core 32F compute route");
|
||||
+
|
||||
+ const ggml_cuda_cublas_route_shape sgemm = ggml_cuda_cublas_route_shape_make(
|
||||
+ /* type */ 0, 0, 12, 12, 1024, 1024, 12, false, false, true, false, false, true, true,
|
||||
+ false, false, false);
|
||||
+
|
||||
+ require(sgemm.route == GGML_CUDA_CUBLAS_ROUTE_SGEMM,
|
||||
+ "cuBLAS records SGEMM fallback route");
|
||||
+
|
||||
+ const int cublas_route_n = ggml_cuda_cublas_route_shape_format(buf, sizeof(buf), bf16_tc);
|
||||
+
|
||||
+ require(cublas_route_n > 0, "cuBLAS route format returns byte count");
|
||||
+ require(std::strstr(buf, "route=bf16_tc") != nullptr, "cuBLAS trace includes route name");
|
||||
+ require(std::strstr(buf, "type=30") != nullptr, "cuBLAS trace includes src0 type");
|
||||
+ require(std::strstr(buf, "src1_type=0") != nullptr, "cuBLAS trace includes src1 type");
|
||||
+ require(std::strstr(buf, "row_diff=18") != nullptr, "cuBLAS trace includes row count");
|
||||
+ require(std::strstr(buf, "src1_ncols=18") != nullptr, "cuBLAS trace includes source column count");
|
||||
+ require(std::strstr(buf, "supports_bf16=1") != nullptr, "cuBLAS trace includes BF16 predicate");
|
||||
+ require(std::strstr(buf, "force_fp32=0") != nullptr, "cuBLAS trace includes forced compute predicate");
|
||||
+ require(std::strstr(buf, "src0_contig=1") != nullptr, "cuBLAS trace includes contiguity predicate");
|
||||
+
|
||||
return 0;
|
||||
}
|
||||
--
|
||||
2.43.0
|
||||
|
||||
Reference in New Issue
Block a user